Interlaced video signals comprise two video fields, one for the odd lines and one for the even lines of an image. This is due to the image capture process, wherein the camera outputs the odd lines at one instant in time and the even lines slightly later. This creates a temporal shift between the odd and even lines of the image, which needs to be addressed in frame based processing systems. A deinterlacing process generally attempts to overcome this problem by assembling a clean frame from the two fields.
Since the temporal shift between the two fields introduce feathering and scintillation artifacts, motion adaptive deinterlacing (MADI) techniques have been proposed in order to reduce such artifacts. Some MADI techniques use local motion threshold values that can be adjusted manually in order to improve the performance of the de-interlacer on a specific problematic video sequence, albeit possibly at the cost of sacrificing the performance (and re-introducing de-interlacing artifacts) in other video sequences.
Therefore, instead of manually adjusting the MADI thresholds in order to “Pass” a specific video sequence, it is desirable to develop a new adaptive system that adjusts the local MADI thresholds automatically and adaptively.